Neural Networks Interview Questions – Set 1

This page represents practice test consisting of objective questions on neural networks. This test can prove to be useful for interviews as well. These questions can prove to be useful for machine learning interns / freshers / beginners.

These questions are related with some of the following topics:

Introduction to neural networks

Perceptron / Sigmoid neuron

Types of neural networks

Cost function for neural networks

Practice Test on Neural Networks

A perceptron can take _______ binary inputs and produces ________ binary outputs?

Multiple, multiple

Multiple, single

Single, multiple

Single, single

Correct!Wrong!

Which of the following type of neurons can take any kind of inputs and not just binary inputs?

Perceptron

Sigmoid

Correct!Wrong!

Which of the following is true for a perceptron?

Output is 0 if w.x + b = 0

Output is 0 if w.x + b = 0

Output is 0 if w.x + b 0

Output is 0 if w.x + b = 0 and 1 if w.x + b >= 0

Correct!Wrong!

In case of perceptrons, which of the following needs to be changed in order to classify inputs in different classes?

Weights

Biases

Both weights and biases

Correct!Wrong!

Which of the following type of neurons can output any real number between 0 and 1 and not just binary outputs?

Perceptron

Sigmoid

Correct!Wrong!

Multilayer networks are also called as ________

Multilayer sigmoid neurons

Multilayer perceptrons

Correct!Wrong!

Neural networks in which output from one layer is fed as input to another layer are called as ________

Feedforward neural networks

Recurrent neural networks

Correct!Wrong!

Neural networks in which information is fed both backward and forward are called as ________

Feedforward neural networks

Recurrent neural networks

Correct!Wrong!

The goal in training a neural network is to find weights and biases which ____________ cost function?

Maximizes

Minimizes

Correct!Wrong!

Neural network with two or more hidden layers can be called as __________

Shallow neural network

Deep neural network

Correct!Wrong!

Which of the following techniques is/are used for training deep neural networks?

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